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Relationships between three major stream assemblages and their environmental factors in multiple spatial scales

Published online by Cambridge University Press:  08 July 2011

Mi-Jung Bae ,
Yongsu Kwon ,
Soon-Jin Hwang ,
Tae-Soo Chon ,
Hyung-Jae Yang ,
In-Sil Kwak ,
Jung-Ho Park ,
Soon-A Ham  and
Young-Seuk Park
Mi-Jung Bae
Affiliation:
Department of Biology, Kyung Hee University, Seoul 130-701, Republic of Korea
Yongsu Kwon
Affiliation:
Department of Biology, Kyung Hee University, Seoul 130-701, Republic of Korea
Soon-Jin Hwang
Affiliation:
Department of Environmental Science, Konkuk University, Seoul 143-701, Republic of Korea
Tae-Soo Chon
Affiliation:
Department of Biological Science, Pusan National University, Busan 609-735, Republic of Korea
Hyung-Jae Yang
Affiliation:
Water Environment Research Department, The National Institute of Environmental Research, Incheon 404-170, Republic of Korea
In-Sil Kwak
Affiliation:
Division of Ocean and Fisheries, Chonman National University, Yosu 500-749, Republic of Korea
Jung-Ho Park
Affiliation:
Dong Lim P&D, Chuncheon 200-701, Republic of Korea
Soon-A Ham
Affiliation:
Department of Biological Science, Chonman National University, Gwangju 500-757, Republic of Korea
Young-Seuk Park*
Affiliation:
Department of Biology, Kyung Hee University, Seoul 130-701, Republic of Korea
*
*Corresponding author: parkys@khu.ac.kr

Abstract

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This study investigated the relationships of three major aquatic assemblages (diatom, macroinvertebrate, and fish) and environmental variables, including sub-basin, hydrology, land cover, and water quality variables on multiple scales. Samples were collected at 720 sampling sites on the Korean nationwide scale. Geological variables, including altitude and slope, showed a strong positive correlation with proportions of forest in land cover types and cobbles in substrates, while they were negatively correlated with water quality variables, including conductivity and total phosphorus. Considering the concordance of the different assemblages, species richness of fish and macroinvertebrates displayed significant correlation, and diatoms were significantly correlated with fish. However, diatoms did not show significant correlation with macroinvertebrates. Altitude and slope showed significant correlation with all biological variables of the three assemblages. Macroinvertebrates and fish showed positive relations with large substrate sizes. Indices of diatoms and macroinvertebrates well reflected the perturbation of water quality variables. However, fish indices showed a relatively low association with water quality variables, compared with those of diatoms and macroinvertebrates. These patterns were also confirmed by the ordination and prediction of biological indices with environmental variables through the learning process of a self-organizing map as well as random forest. Overall, our study supports the concept of multi-scale habitat filters and functional organization in streams, and is consistent with the recommended use of multiple biological indices with more than one assemblage for the assessment of the biotic integrity of aquatic ecosystems.

Keywords

Multimetricconcordance of taxabiological indicesself-organizing maprandom forest
Type
Research Article
Information
Annales de Limnologie - International Journal of Limnology , Volume 47 , Issue S1: River ecosystem health assessment: the value in the management and restoration , 2011 , pp. S91 - S105
Copyright
© EDP Sciences, 2011

References

Allan, J.D. and Castillo, M.M., 2007. Stream Ecology: Structure and Function of Running Waters, 2nd edn., Kluwer Academic Publishers, Boston, 436 p.CrossRefGoogle Scholar
Allan, J.D., Erickson, D.L. and Fay, J., 1997. The influence of catchment land use on stream integrity across multiple spatial scales. Freshwater Biol., 37, 149–161.CrossRefGoogle Scholar
Allen, A.P., Whittier, T.R., Larsen, D.P., Kaufmann, P.R., O'Connor, R.J., Hughes, R.M., Stemberger, R.S., Dixit, S.S., Brinkhurst, R.O., Herlihy, A.T. and Paulsen, S.G., 1999. Concordance of taxonomic composition patterns across multiple lake assemblages: effects of scale, body size, and land use. Can. J. Fish. Aquat. Sci., 56, 2029–2040.CrossRefGoogle Scholar
American Public Health Association (APHA), American Water Works Association (AWWA), Water Environment Federation (WEF), 2005. Standard Methods for the Examination of Water and Wastewater: Contennial Edition (Standard Methods for the Examination of Water and Wastewater), 21th edn., American Public Health Association, Washington, DC.
An, K.G. and Lee, E.H., 2006. Ecological health assessments of Yoogu stream using a fish community metric model. Korean J. Limnol., 39, 310–319.Google Scholar
Angermeier, P.L. and Schlosser, I.J., 1989. Species–area relationship for stream fishes. Ecology, 70, 1450–1462.CrossRefGoogle Scholar
Armitage, P.D., Moss, D., Wright, J.F. and Furse, M.T., 1983. The performance of a new biological water quality score system based on macroinvertebrates over a wide range of unpolluted running water sites. Water Res., 17, 333–347.CrossRefGoogle Scholar
Barbour, M.T., Gerritsen, J., Snyder, B.D. and Stribling, J.B., 1999. Rapid Bioassessment Protocols for Use in Streams and Wadeable Rivers: Algal, Benthic Macroinvertebrates, and Fish, 2nd edn., EPA 841-B-99-002, U.S. Environmental Protection Agency, Office of Water, Washington, DC.Google Scholar
Beyer, J., 1996. Fish biomarkers in marine pollution monitoring; evaluation and validation in laboratory and field studies, Academic Thesis, University of Bergen, Norway.
Black, R.W., Munn, M.D. and Plotnikoff, R.W., 2004. Using macroinvertebrates to identify biota- and cover optima at multiple scales in the Pacific Northwest, USA. J. N. Am. Benthol. Soc., 23, 340–362.2.0.CO;2>CrossRefGoogle Scholar
Breiman, L., 2001. Random forests. Mach. Learn., 45, 5–32.CrossRefGoogle Scholar
Carter, J.L., Fend, S.V. and Kennelly, S.S., 1996. The relationships among three habitat scales and stream benthic invertebrate community structure. Freshwater Biol., 35, 109–124.CrossRefGoogle Scholar
DIN 38410, 1990. German standard methods for the examination of water, waste water and sludge: Biological-ecological examination of water (group M): Procedure for the determination of the saprobic index on the basis of benthic communities (M2), Deutsches Institut für Normung E.V., Berlin, 10 p.
Duong, T.T., Feirtet-Mazel, A., Coste, M., Dang, D.K. and Boudou, A., 2007. Dynamics of diatom colonization process in some rivers influenced by urban pollution. Ecol. Indic., 7, 839–851.CrossRefGoogle Scholar
European Commission, 2000. Directive 2000/60/EC of the European Parliament and of the Council establishing a framework for Community action in the field of water policy. Off. J. Eur. Comm., L327, 1–72.
Flinders, C.A., Horwitz, R.J. and Belton, T., 2008. Relationship of fish and macroinvertebrate communities in the mid-Atlantic uplands: Implications for integrated assessments. Ecol. Indic., 8, 588–598.CrossRefGoogle Scholar
Frissell, C.A., Liss, W.J., Warren, C.E. and Hurley, M.D., 1986. A hierarchical framework for stream habitat classification: viewing streams in a watershed context. Environ. Manage., 10, 199–214.CrossRefGoogle Scholar
Gorman, O.T. and Karr, J.R., 1978. Habitat structure and stream fish communities. Ecology, 59, 507–515.CrossRefGoogle Scholar
Gregory, S.V., Swanson, F.J. and Mckee, W.A., 1991. An ecosystem perspective of riparian zones. BioScience, 41, 540–551.CrossRefGoogle Scholar
Grenouillet, G., Broe, S., Tudesque, L., Lek, S., Baraillé, Y. and Loot, G., 2007. Concordance among stream assemblages and spatial autocorrelation along a fragmented gradient. Divers. Distrib., 14, 592–603.CrossRefGoogle Scholar
Griffith, M.B., Hillb, B.H., McCormick, F.H., Kaufmannd, P.R., Herlihye, A.T. and Sellef, A.R., 2005. Comparative application of indices of biotic integrity based on periphyton, macroinvertebrates, and fish to southern Rocky Mountain streams. Ecol. Indic., 5, 117–136.CrossRefGoogle Scholar
Heino, J., Paavola, R., Virtanen, R. and Muotka, T., 2005. Searching for biodiversity indicators in running waters: do bryophytes, macroinvertebrates, and fish show congruent diversity patterns? Biodivers. Conserv., 14, 415–428.CrossRefGoogle Scholar
Hering, D., Johnson, R.K., Kramm, S., Schmutz, S., Szoszkiewicz, K. and Verdonschot, P.F.M., 2006. Assessment of European streams with diatoms, macrophytes, macroinvertebrates and fish: a comparative metric-based analysis of organism response to stress. Freshwater Biol., 51, 1757–1785.CrossRefGoogle Scholar
Infante, D.M., Allan, J.D., Linke, S. and Norris, R.H., 2009. Relationship of fish and macroinvertebrate assemblages to environmental factors: implications for community concordance. Hydrobiologia, 623, 87–103.CrossRefGoogle Scholar
Jain, A.K. and Dubes, R.C., 1988. Algorithms for Clustering Data, Prentice Hall, Englewood Cliffs, NJ, 304 p.Google Scholar
Johnson, R.K., Furse, M.T., Hering, D. and Sandin, L., 2007. Ecological relationships between stream communities and spatial scale: implications for designing catchment level monitoring programmes. Freshwater Biol., 52, 939–958.CrossRefGoogle Scholar
Justus, B.G., Petersen, J.C., Femmer, S.R., Davis, J.V. and Wallace, J.E., 2010. A comparison of algal, macroinvertebrate, and fish assemblage indices for assessing low-level nutrient enrichment in wadeable Ozark streams. Ecol. Indic., 10, 627–638.CrossRefGoogle Scholar
Karr, J.R., 1981. Assessment of biotic integrity using fish communities. Fisheries, 66, 21–71.2.0.CO;2>CrossRefGoogle Scholar
Kelly, M.G. and Whitton, B.A., 1995. The trophic diatom index: a new index for monitoring eutrophication in rivers. J. Appl. Phycol., 7, 433–444.CrossRefGoogle Scholar
Kohonen, T., 2001. Self-Organizing Maps, 3rd edn., Springer, Berlin, 501 p.CrossRefGoogle Scholar
Lenat, D.R. and Crawford, J.K., 1994. Effects of land use on water quality and aquatic biota of three North Carolina Piedmon streams. Hydrobiologia, 294, 185–199.CrossRefGoogle Scholar
Liaw, A. and Wiener, M., 2002. Classification and regression by randomForest. R News, 2, 18–22.Google Scholar
Melo, A.S. and Froehlich, C.G., 2001. Macroinvertebrates in neotropical streams: richness patterns along a catchment and assemblage structure between 2 seasons. J. N. Am. Benthol. Soc., 20, 1–16.CrossRefGoogle Scholar
MOE/NIER, 2008. The survey and evaluation of aquatic ecosystem health in Korea. The Ministry of Environment/National Institute of Environmental Research, Incheon, Korea (in Korean with English summary).
Paavola, R., Muotka, T., Virtanen, R., Heino, J. and Kreivi, P., 2003. Are biological classifications of headwater streams concordant across multiple taxonomic groups? Freshwater Biol., 48, 1912–1923.CrossRefGoogle Scholar
Paavola, R., Muotka, T., Virtanen, R., Heino, J., Jackson, D. and Mäki-Petäys, A., 2006. Spatial scale affects community concordance among fishes, benthic macroinvertebrates, and bryophytes in streams. Ecol. Appl., 16, 368–379.CrossRefGoogle ScholarPubMed
Park, Y.S., Chang, J., Lek, S., Cao, W. and Brosse, S., 2003. Conservation strategies for endemic fish species threatened by the Three Gorges Dam. Conserv. Biol., 17, 1748–1785.CrossRefGoogle Scholar
Park, Y.-S., Song, M.-Y., Park, Y.-C., Oh, K.-H., Cho, E. and Chon, T.-S., 2007. Community patterns of benthic macroinvertebrates collected on the national scale in Korea. Ecol. Model., 203, 26–33.CrossRefGoogle Scholar
Poff, N.L.R., 1997. Landscape filters and species traits: towards mechanistic understanding and prediction in stream ecology. J. N. Am. Benthol. Soc., 16, 391–409.CrossRefGoogle Scholar
Poff, N.L.R. and Allan, J.D., 1995. Functional organization of stream fish assemblages in relation to hydrological variability. Ecology, 76, 606–627.CrossRefGoogle Scholar
Poff, N.L.R. and Ward, J.V., 1990. Physical habitat template of lotic systems: Recovery in the context of historical pattern of spatiotemporal heterogeneity. Environ. Manage., 14, 629–645.CrossRefGoogle Scholar
Quinn, J.M., Steele, G.L., Hickey, C.W. and Vickers, M.L., 1997. Land use effects on habitat, water quality, periphyton, and benthic invertebrates in Waikato, New Zealand, hill-country streams. N. Z. J. Mar. Freshwater Res., 28, 391–397.CrossRefGoogle Scholar
Richards, C., Haro, R.J., Johnson, L.B. and Host, G.E., 1997. Catchment and reach-scale properties as indicators of macroinvertebrate species traits. Freshwater Biol., 37, 219–230.CrossRefGoogle Scholar
Rott, E., 1991. Methodological aspects and perspectives in the use of periphyton for monitoring and protecting rivers. In: Whitton, B.A., Rott, E. and Friedrich, G. (eds.), Use of Algae for Monitoring Rivers, Institut für Botanik, University of Innsbruck, Austria, 9–16.Google Scholar
Sponseller, R.A., Benfield, E.F. and Valett, H.M., 2001. Relationships between land use, spatial scale and stream macroinvertebrate communities. Freshwater Biol., 46, 1409–1424.CrossRefGoogle Scholar
StatSoft Inc., 2004. STATISTICA (data analysis software system), version 7. www.statsoft.com.
Stevenson, R.J. and Pan, Y., 1999. Assessing ecological conditions in rivers and streams with diatoms. In: Stoermer, E.F. and Smol, J.P. (eds.), The Diatoms: Applications to the Environmental and Earth Sciences, Cambridge University Press, Cambridge, UK, 11–40.CrossRefGoogle Scholar
Tang, T., Cai, Q. and Liu, J., 2006. Using epilithic diatom communities to assess ecological condition of Xiangxi River system. Environ. Monit. Assess., 112, 347–361.CrossRefGoogle ScholarPubMed
Tonn, W.M., Magnuson, M.R. and Toivonen, J., 1990. Intercontinental comparison of small-lake fish assemblages: the balance between local and regional processes. Am. Nat., 136, 345–375.CrossRefGoogle Scholar
Townsend, C.R., 1996. Concepts in river ecology: pattern and process in the catchment hierarchy. Arch. Hydrobiol. Suppl., 113, 3–21.Google Scholar
Townsend, C.R., 2003. Individual, population, community, and ecosystem consequences of a fish invader in New Zealand streams. Conserv. Biol., 17, 1, 38–47.CrossRefGoogle Scholar
Townsend, C.R. and Hildrew, A.G., 1994. Species traits in relation to a habitat templet for river systems. Freshwater Biol., 31, 265–275.CrossRefGoogle Scholar
Ultsch, A., 1993. Self-organizing neural networks for visualization and classification. In: Opitz, B., Lausen, O. and Klar, R. (eds.), Information and Classification, Springer-Verlag, Berlin, 307–313.CrossRefGoogle Scholar
US EPA, 2002. Biological Assessments and Criteria Crucial Components of Water Quality Programs, U.S. Environmental Protection Agency, Office of Water, EPA 822-F-02-006, Washington, DC.
Vannote, R.L., Minshall, G.W., Cummins, K.W., Sedell, J.R. and Cushing, C.E., 1980. The river continuum concept. Can. J. Fish. Aquat. Sci., 37, 130–137.CrossRefGoogle Scholar
Walley, W.J. and Hawkes, H.A., 1997. A computer-based development of the Biological Monitoring Working Party score system incorporating abundance rating, site type and indicator value. Water Res., 31, 201–210.CrossRefGoogle Scholar
Watanabe, T., Asai, K. and Houki, A., 1986. Numerical estimation of organic pollution of flowing water by using the epilithic diatom assemblage – Diatom Assemblage Index (DAIpo). Sci. Total Environ., 55, 209–218.CrossRefGoogle Scholar
Won, D.H., Jun, Y.C., Kwon, S.J., Hwang, S.J., Ahn, K.G. and Lee, J.W., 2006. Development of Korean saprobic index using benthic macroinvertebrates and its application to biological stream environment assessment. J. Korean Soc. Water Qual., 22, 768–783 (in Korean with English summary).Google Scholar
Zelinka, M. and Marvan, P., 1961. Zur Präzisierung der biologischen Klassifikation der Reinheit fließender Gewässer. Arch. Hydrobiologia, 57, 389–407.Google Scholar